Fahimeh Mirzaee; Majid Jalali Farahani; Amin Ghazi Zahedi; Ghodratollah Bagheri
Abstract
The study is to designing a model to predict the success of countries participating in the 2018 FIFA World Cup Russia. This study was conducted on two qualitative (setting indices) and quantitative (collecting data from selected countries) steps. Semi-structured qualitative and depth interviews was conducted ...
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The study is to designing a model to predict the success of countries participating in the 2018 FIFA World Cup Russia. This study was conducted on two qualitative (setting indices) and quantitative (collecting data from selected countries) steps. Semi-structured qualitative and depth interviews was conducted with 24 elites that aware of the issue of study with non-randomly and purposeful procedure.After identifying indexes, information of selected Indexes (26 Indexes of the political, economic, social, cultural, technological and sporting as theoretical model (PEST+ S)) was collected for 38 countries that were selected with non-randomly and Available procedure since 1978 Argentina FIFA World Cup to 2014 Brazil. On the next step, the predicted 26 indexes were compared with actual values in 2010 and 2014 to test the conceptual model. The results showed that MLP method was of less error at predicting the 26 indexes. In final step, 26 indexes in 2018 were estimated and position of selected countries was predicted in 2018 FIFA World Cup Russia.According to MLP results, Islamic Republic of Iran, Japan and South Korea, with position of 1 from the Asian continent will qualify to FIFA World Cup. Also, Belgium and Portugal will ascend to the semifinals, according the predicted position of 4.
Hossain Zareian; Alireza Elahi; Sajadi Seyyed Nasrollah; Amin Ghazi Zahedi
Volume 14, Issue 30 , August 2016, , Pages 37-54
Abstract
The aim of the study was prediction of countries’ success that participating in the 2016 Olympic Games in Rio de Janeiro with intelligent method of MLP. This study was conducted on two qualitative (setting indices) and quantitative (collecting data from selected countries) steps. In the first phase, ...
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The aim of the study was prediction of countries’ success that participating in the 2016 Olympic Games in Rio de Janeiro with intelligent method of MLP. This study was conducted on two qualitative (setting indices) and quantitative (collecting data from selected countries) steps. In the first phase, non-randomly and purposeful procedure, semi-structured qualitative and depth interviews was conducted with 28 elites that were aware of the issue of study up to theoretical saturation. After identification of indexes, Information of selected indicators (22 Indexes political, economic, social, cultural, technological and sporting as Theoretical Model (PEST+S)) was collected for 42 selected countries, in 40-years period, since 1976 Montreal Olympics to 2012 London. On the next step, from test of the conceptual model of multilayer perceptron networks (MLP) were used in comparison the actual values of Iran’s 22 indexes with predicted values in 2012. The results showed, in comparison the actual values with predicted values in 2012, the MLP has small errors in predicting of indices. Also, comparison of actual rank and predicted rank of 42 selected countries in 2012, MLP method had less Mean absolute error rate (0.4629). In final step, indices were estimated and rank of selected countries was predicted in Rio de Janeiro (2016). According to research results, Countries United States of America, China and the Great Britain will be in the first to third places, in 2016 Olympic Games. Also, Islamic Republic of Iran will be in 21st place among participating teams. Generally, using of Neural Networks Model, Iranian sport Policymaker’s can use identified indices to planning for successful participation in the Olympic Games.